Literature Review in Consumer Neuroscience for Product Design

Literature Review in Consumer Neuroscience for Product Design Chenjie Wang Advanced Manufacturing Institute, Hong Kong University of Science and Technology Abstract: The ultimate goal of design is to meet customer needs. To achieve this goal, it is critical to understand customer’s complete needs and perceived values. The technology and equipment in neuroscience such as functional near-infrared spectroscopy (fNIRS) has been applied as a complementary tool for product designers to identify customer’s unconscious preference and articulated needs. The research progress in consumer neuroscience and neuromarketing has shown that the neuro-imaging technologies are able to identify customer’s cognitive and affective responses to the product or brands through measuring his/her cerebral activities. This sheds light on its potentials of the applications to product design research. This paper review current status of consumer neuroscience for product design practice. Keywords: Product design, neuroscience, preferences 1. Intoduction Product design is the process of capturing and transforming customer needs into a tangible product specification that designers can follow (Chen et al., 2009). The ultimate goal of design is to meet customer needs. To achieve this goal, it is critical to understand customer’s complete needs and perceived values (Wang et al., 2007, 2012). Customer’s perceived value depends on not only product’s admired utilitarian functions, but also the entire experience with the products. Thus, current design trends have been moving from design for products’ utilitarian functions to capture customer’s various levels of needs. According to the hierarchy nature of human needs, customer’s needs are classified as articulated needs and unarticulated needs (Wang et al., 2013a). Articulated needs can be well verbalized and represented in an objective and well elaborated form. The characterization, quantification and representation of articulated needs have been well addressed by the conventional customer needs identifications, such as conjoint analysis, voice of customers etc. However, unarticulated needs are those latent and hedonic related high-level needs that customers are not able to clearly express to the designers. Sometimes customers don’t even know what they really want. Thus the goal of meeting customers’ unarticulated needs often can’t be expressed in objective and quantitative terms entirely. It restricts the possibility of exploring, assessing, and optimizing different alternatives. It is obvious that there is a need to discover new ways to elicit, characterize and incorporate the comprehensive customer needs into design. In order to identify those needs, designers should carefully learn about consumer’s memories as well

as current and ideal experience with the methods such as contextual inquiry. The technology and equipment in neuroscience such as functional near-infrared spectroscopy (fNIRS) has been applied as a complementary tool for product designers to identify customer’s unconscious preference and articulated needs. The research progress in consumer neuroscience and neuromarketing has shown that the neuro-imaging technologies are able to identify customer’s cognitive and affective responses to the product or brands through measuring his/her cerebral activities. This sheds light on its potentials of the applications to product design research. 2. Unarticulated Needs Identification There are many methods in engineering to identify customer needs, such as conjoint analysis, QFD, configurators (Green et al., 1978; Wang et al., 2011, 2013b). Applied ethnography is proposed as ethnographic field work done to bring the consumer’s point of view to the new product design as well as existing product improvement (Sanders 2002). The applied ethnography basically includes contextual inquiry, observational research and participant observation. This type of research takes place in natural surroundings where the product is used, and it has a goal which is more likely to be exploratory rather than evaluative. Applied ethnography can be employed throughout the new product development process, and it is considered most useful in exploring emerging and unmet needs for a particular target consumer group. Kansei engineering is another type of technology to capture consumer’s image and feelings relevant to a product. Kansei in Japanese means a consumer’s psychological feelings and image regarding to a new product. Thus, Kansei Engineering is defined as “translating technology of a consumer’s feeling of the product to the design elements.” (Nagamachi 1995) The basic idea is to describe the product concept from two different perspectives: the semantic description and the description of product properties. The two descriptions span a vector space separately, and then are merged with each other in the synthesis phase, which means which of the product properties evokes which semantic impact. (Simon, Schuttet et al. 2004) In practice, Kansei engineering starts from collecting the psychological feelings, including emotions, moods, and impressions, through Semantic Differential Method. Then, the kansei words are input to the Kansei engineering system which employs an expert system and databases. In the system, these words are recognized in reference to the kansei word databases, matched to the image database, and calculated by an inference engine to find the best-fit design, which will be shown on the display of the computer. This kind of kansei engineering system is very helpful for the customer to select the product most fitted to his/her kansei. (Nagamachi 2002; Dahlgaard, Schütte et al. 2008) Affective computing has been introduced to human-computer interface design to recognize the user’s affect dynamically to the computer’s design suggestions (Picard 1995). This type of

concepts can also be easily extended to the product design. It is considered that a desired design can bring the user to a new state that feels better than the one the user was in, as the design may inspires the user or solve a problem to make the user feel relief. Different from Kansei engineering which depends on the consumer’s verbal expression of their feelings, affective computing can directly recognize the user’s sentic responses which have the advantage of not having to be translated to language. Currently, there have been a lot of mobile electrodermal activity and motion sensors developed and commercialized that can directly or indirectly measure users’ emotion state by capturing physiological changes (Picard 2010). The designers are considered to be benefited from studying the association between the sentic response and design (Picard 1995). The frontal lobes is an important region of the brain dealing with cognitive behavior and action planning (Ambler, Ioannides et al. 2000). In particular, the ventro-medial frontal lobe is crucial for decision-making (Damasio 1994). It is suggested that decision-making is more associated with feelings than thinking and is co-located with the processing of secondary level emotions and in the context of past experience. Note: Ventromedial frontal cortex is used interchangeably with orbitofrontal cortex in many literatures, such as in (Rilling, Gutman et al. 2002). Orbitofrontal Cortex The orbitofrontal cortex (OFC) and the closely related ventromedial prefrontal cortex have been shown to code the perceived value of different possible outcomes (Wallis and Miller 2003). The studies in neuroimaging, neuropsychology and neurophysiology indicate that the OFC is a nexus for sensory integration, the modulation of autonomic reactions, and participation in learning, prediction and decision making for emotional and reward-related behaviors (Kringelbach 2005). The OFC calculates how rewarding a reward is. The value signal can then be held in working memory where it can be used by lateral prefrontal cortex to plan and organize behavior toward obtaining the outcome, and by medial prefrontal cortex to evaluate the overall action in terms of its success and the effort that was required. Acting together, these prefrontal areas can ensure that our behavior is most efficiently directed towards satisfying our needs (Wallis 2007). The lateral area of the OFC is found activated following a punishing outcome, such as losing money, and the medial OFC is activated following a rewarding outcome, such as receiving money (O'Doherty, Kringelbach et al. 2001). The magnitude of the activations reflects the magnitude of the reward or punishment delivered. The medial region that showed increased activation to reward also showed decreased BOLD signal when punishment was delivered, and vice versa for the lateral OFC region (the experiment was conducted with fMRI). Medial OFC is also found associated with willingness to pay, the value of goals in decision

making (Plassmann, O'Doherty et al. 2007). In a study in hungry subjects who placed real bids for the right to eat different foods, the subjects’ brain fMRI that activity in the right medial OFC and dorsolateral prefrontal cortex encode for WTP in everyday economic decisions. More specifically, the result showed increasing activation with WTP in the free trials and significantly more activated in the free trials than in the forced trials. (In the free trials, the subject can bid the WTP, while in the forced trials, the subject should bid the told number, in order to eliminate other variables correlated with the activity, such as anticipatory taste.) However, this study cannot show whether the medial OFC can also encode the value of nonprimary rewards (food is a primary appetitive reward) and of negative or undesirable items. The study also showed the overlap in the neuronal properties, which cannot be further studied by the experimental design. OFC is found associated with the expectation of a pleasant taste and reward receipt (O'Doherty, Deichmann et al. 2002). When the human subjects were presented with visual cues that signaled subsequent reinforcement with a pleasant sweet taste, a moderately unpleasant salt taste, or a neutral taste, the expectation of a pleasant taste produced activation in dopaminergic midbrain, posterior dorsal amygdala, striatum and OFC. However, except for OFC, those regions are not activated by reward receipt. The activation of OFC is associated with mutual cooperation (Rilling, Gutman et al. 2002). In a study of iterated Prisoner’s Dilemma Game, consistent activation in brain areas that have been linked with reward processing: nucleus accumbens, the caudate nucleus, OFC, and rostral anterior cingulate cortex. It is proposed that activation of this neural network positively reinforces reciprocal altruism, thereby motivating subjects to resist the temptation to selfishly accept but not reciprocate favors. The activation of medial OFC (mOFC) is found associated with experienced pleasantness (Plassmann, O'Doherty et al. 2008). It is proposed that marketing actions, such as changes in the price of a product, can affect neural representations of experienced pleasantness. In a wine test study, it is assumed that the individual is likely to believe that a more expensive wine will probably test better. The study result is consistent with the hypothesis, and the activity in the mOFC is correlated with absolute reports of pleasantness. No evidence was found for an effect of prices on areas of the primary taste areas, so it possibly means that top-down cognitive processes that encode the flavor expectancies are integrated with the bottom-up sensory components of the wine in the mOFC, thus modulating the hedonic experience of flavor. In the economic choice, the neurons in the OFC are found encoding the value of offered and chosen goods (Padoa-Schioppa and Assad 2006). Notably, OFC neurons encode value independently of visuospatial factors and motor responses. If a monkey chooses between A and B, neurons in the OFC encode the value of the two goods independently of whether A is presented on the right and B on the left, or vice versa. This trait distinguishes the OFC from other brain areas in

which value modulates activity related to sensory or motor processes. The VMPFC, particularly medial frontal gyrus, is found playing a critical role in preference judgments, and the finding is consistent with the role of the VMPFC in the representation of the complex somatic states that are difficult to verbalize but have a powerful influence on which response is liked best (Paulus and Frank 2003). The activation of the VMPFC/OFC is found associated with reflexive system (or called X-system), which automatically codes the trait and evaluative implications of observed behaviors (Satpute and Lieberman 2006). In comparison, reflection system (C-system) is responsible for holding inferential goals in mind and for taking situational constraint information and other prior knowledge into account to alter the dispositional inferences drawn from observed behaviors. The activation of OFC is found associated with the social reinforcers, such as sports cars. The study in evaluating different categories of cars (Erk, Spitzer et al. 2002) revealed significantly more activation in ventral striatum, orbitofrontal cortex, anterior cingulate and occipital regions for sports cars in contrast to other categories of cars, which demonstrates that artificial cultural objects associated with wealth and social dominance elicit activation in reward-related brain areas. (social reinforcers, such as sports cars is possibly processed with X-system, so VMPFC is activated).

Prefrontal Cortex/Dorsolateral Prefrontal Cortex The prefrontal cortex (PFC) is well positioned to coordinate a wide range of neuroprocess: a collection of interconnected neocortical areas that sends and receives projections from virtually all cortical sensory systems, motor systems, and many subcortical structures (Miller and Cohen 2001). The PFC is important when “top-down” processing is needed; that is, when behavior must be guided by internal states and intentions. It is critical in the situations when the mappings between sensory inputs, thoughts, and actions either are weakly established relative to other existing ones or are rapidly changing. For instance, when naming the color of a conflicting stimulus (e.g. the word GREEN displayed in red) (MacLeod 1991), the patients with frontal impairment have difficulty with such tasks (Vendrell, Junqué et al. 1995). The dorsolateral prefrontal cortex (DLPFC) is more directly interconnected with sensory and motor system structures and is considered to be more involved in cognitive functions, such as attention, working memory and response selection than in dealing with the external world (Wallis and Miller 2003). It is found that DLPFC and OFC are characterized by a large degree of overlap in the neuronal

properties, which suggests a great deal of exchange and communication between them (Wallis and Miller 2003). In addition, the study results found in (Wallis and Miller 2003) suggest that the OFC may be a source of reward signals to the DLPFC, and many neuropsychological studies have pointed to the relative importance of the OFC for tasks that require assessment of reward value. DLPFC is found associated with exercising self-control, which is required to make optimal decision when individuals make choices between an alternative with higher overall value and a more tempting but ultimately inferior opinion (Hare, Camerer et al. 2009). In a study of subjects’ rating on 50 different food items of taste and health separately, the results suggest that self-control problems arise in situations where various factors must be integrated in the OFC to compute goal values, which is the short-term value of the stimuli, and that DLPFC activity is required for higher-order factors to be incorporated into the OFC value signal, which represents incorporating the long-term considerations into values. Thus, DLPFC influences self-control by modulating the value signal encoded in OFC. The DLPFC is implicated in modifying behavior based on emotion and affect (McClure, Li et al. 2004). Lesions to the DLPFC may result in depression which is hypothesized to result from a decreased ability to use positive affect to modify behavior. The DLPFC is necessary for employing affective information in biasing behavior. The study results in (McClure, Li et al. 2004) show that labeling Coke in taste and imaging tasks both biases behavior and recruits DLPFC activity, but both of these effects are lost when compared with the semianoymous Pepsi tasks. Lesion and neuroimaging studies suggest that DLPFC play an important role in regulating the processing of visual sexual stimulation. A fNIRS study (Leon-Carrion, Martin-Rodriguez et al. 2007) exploring DLPFC structures involved in the processing of erotic and non-sexual films showed that a sexual stimulus would produce DLPFC activation during the period of direct stimulus perception (“on” period), and that this activation would continue after stimulus cessation, while the exposure to the non-sexual scene did not produce strong activation of DLPFC. Thus, the study suggests that DLPFC plays a critical role in the self-regulation of sexual arousal. In some studies examining self-recognition, greater activities in right lateral PFC were observed when individuals identify pictures as themselves compared with when they identify pictures of familiar others (Lieberman 2007).

Medial Prefrontal Cortex The medial prefrontal cortex (MPFC) is concerned with determining future behavior on the basis of anticipated value. In particular, it is associated with meta-cognitive representations that enable us to reflect on the values linked to outcomes and actions, in other words, thinking about thinking.

These high level representations have a major role in many aspects of social cognition, which allow us to reflect on the values that other people attach to actions and outcomes as well as what other people think about us. The tasks shown to activate the MPFC roughly comprise three different categories: self-knowledge, person knowledge and mentalizing (Amodio and Frith 2006). Reflecting on one’s current experience leads to remarkably consistent activation of MPFC across a variety of different tasks (Lieberman 2007). The studies that most directly isolate the act of self-reflection have examined neural response occurring when participants indicate their current emotional response to a picture compared with making a non-self-relevant judgment. The increases in MPFC activity were also observed when participants rated their own emotional reaction to emotional stimuli (Taylor, Phan et al. 2003). The activations of the MPFC and VMPFC are found present only in autobiographical memory retrieval, while right DLPFC is present primarily in episodic memory retrieval (Gilboa 2004). The autobiographic memory tends to be filled with events of personal significance, rather than a linear record of events over time. The medial activations associated with autobiographical memories may result from these memories being linked to one’s internal sense of self and the feelings one had during the events (Lieberman 2007). In the studies of reflection on one’s own self-concept in trait terms, such as kind, and smart, the activation of the MPFC were great during the self-judgments task than the nonsocial control task, and several also report greater MPFC during self-judgments than during other social judgments (Lieberman 2007). These studies are remarkably consistent in identifying activity in a medial frontoparietal network when individuals reflect on their own psychological make-up, an internally-focused process.

fNIRS studies In a study exploring the human product-preference relationship, fNIRS was used to measure the basis of change in the oxygenated hemoglobin concentration in VMPFC (Shimokawa, Misawa et al. 2008). A Bayesian three-layer perception was used as a prediction model. The result reveals that the activation of the VMPFC provides beneficial information with regard to product-preference relationship. In addition, this study also indicates that fNIRS has the capability to identify individual’s preference with brain data at a shallow depth. An NIR-BCI paradigm is proposed in (Luu and Chau 2009) based on directly decoding neural correlates of decision making, especially subjective preference evaluation. Different drinks are used for individual’s preference identification. In the study, the preference was collected before the measurement, and only unequally ranked pairs were selected in the fNIRS studies. Using mean

signal amplitudes as features and linear discriminant analysis, the authors were able to decode the preference on a single-trial basis with an average accuracy of 80%. 3. Conclusion We believe that neuroscience technology can lead us to better understand the nature of the unarticulated customer needs. Potential breakthrough in characterizing and eliciting of unarticulated customer needs can be made. There is a possibility that diverse design approaches among engineering, neuroscience, human factor and cognitive science can be establishes in a holistic way.

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